scholarly journals The human claustrum is functionally connected to cognitive networks and involved in cognitive control

2018 ◽  
Author(s):  
Samuel R. Krimmel ◽  
Michael G. White ◽  
Matthew H. Panicker ◽  
Frederick S. Barrett ◽  
Brian N. Mathur ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Control ◽  
Resting State ◽  
Cognitive Task ◽  
Cognitive Networks ◽  
Anterior Cingulate ◽  
Mammalian Brain ◽  
List Type ◽  
Sensorimotor Processing ◽  
Difficult Condition

AbstractThe claustrum is among the most highly connected structures in the mammalian brain. However, the function of the claustrum is unknown, which is due to its peculiar anatomical arrangement. Here, we use resting state and task functional magnetic resonance imaging (fMRI) to elucidate claustrum function in human subjects. We first describe a method to reveal claustrum signal with no linear relationship with adjacent regions. We applied this approach to resting state functional connectivity (RSFC) analysis of the claustrum at high resolution (1.5 mm isotropic voxels) using a 7T dataset (n=20) and a separate 3T dataset for replication (n=35). We then assessed claustrum activation during performance of a cognitive task, the multi-source interference task, at 3T (n=33). Extensive functional connectivity was observed between claustrum and cortical regions associated with cognitive control, including anterior cingulate, prefrontal and parietal cortices. Cognitive task performance was associated with widespread activation and deactivation that overlapped with the cortical areas showing functional connectivity to the claustrum. Furthermore, the claustrum was significantly activated at the onset of the difficult condition of the task, but not during the remainder of the difficult condition. These data suggest that the claustrum can be functionally isolated with fMRI, and that it is involved in cognitive control in humans independent of sensorimotor processing.HighlightsRemoving signal from neighboring structures isolates claustrum BOLD signal at 7T and 3T field strengthClaustrum is extensively functionally connected with cortex, including cognitive networksClaustrum is activated at the onset of a cognitive conflict taskClaustrum may be involved in cognition independent of sensorimotor processing

scholarly journals Tonic resting-state hubness supports high-frequency activity defined verbal-memory encoding network in epilepsy

2019 ◽  
Author(s):  
Chaitanya Ganne ◽  
Walter Hinds ◽  
James Kragel ◽  
Xiaosong He ◽  
Noah Sideman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Verbal Memory ◽  
Resting State ◽  
High Frequency ◽  
Cognitive Networks ◽  
Gamma Activity ◽  
List Type ◽  
Healthy Controls ◽  
Memory Encoding ◽  
Memory Network

AbstractHigh-frequency gamma activity of verbal-memory encoding using invasive-electroencephalogram coupled has laid the foundation for numerous studies testing the integrity of memory in diseased populations. Yet, the functional connectivity characteristics of networks subserving these HFA-memory linkages remains uncertain. By integrating this electrophysiological biomarker of memory encoding from IEEG with resting-state BOLD fluctuations, we estimated the segregation and hubness of HFA-memory regions in drug-resistant epilepsy patients and matched healthy controls. HFA-memory regions express distinctly different hubness compared to neighboring regions in health and in epilepsy, and this hubness was more relevant than segregation in predicting verbal memory encoding. The HFA-memory network comprised regions from both the cognitive control and primary processing networks, validating that effective verbal-memory encoding requires multiple functions, and is not dominated by a central cognitive core. Our results demonstrate a tonic intrinsic set of functional connectivity, which provides the necessary conditions for effective, phasic, task-dependent memory encoding.HighlightsHigh frequency memory activity in IEEG corresponds to specific BOLD changes in resting-state data.HFA-memory regions had lower hubness relative to control brain nodes in both epilepsy patients and healthy controls.HFA-memory network displayed hubness and participation (interaction) values distinct from other cognitive networks.HFA-memory network shared regional membership and interacted with other cognitive networks for successful memory encoding.HFA-memory network hubness predicted both concurrent task (phasic) and baseline (tonic) verbal-memory encoding success.

scholarly journals The role of neural flexibility in cognitive aging

2021 ◽  
Author(s):  
Eleanna Varangis ◽  
Weiwei Qi ◽  
Yaakov Stern ◽  
Seonjoo Lee
Keyword(s):  
Functional Connectivity ◽  
Cognitive Performance ◽  
Resting State ◽  
Cognitive Aging ◽  
Cognitive Task ◽  
Cognitive Networks ◽  
Cognitive Outcomes ◽  
Matrix Reasoning ◽  
Flexibility Measures ◽  
And Task

AbstractStudies assessing relationships between brain and cognitive changes in healthy aging have shown that a variety of aspects of brain structure and function explain a significant portion of the variability in cognitive outcomes throughout adulthood. Many studies assessing relationships between brain function and cognition have utilized time-averaged, or static functional connectivity methods to explore ways in which brain network organization may contribute to aspects of cognitive aging. However, recent studies in this field have suggested that time-varying, or dynamic measures of functional connectivity, which assess changes in functional connectivity throughout a scan session, may play a stronger role in explaining cognitive outcomes in healthy young adults. Further, both static and dynamic functional connectivity studies suggest that there may be differences in patterns of brain-cognition relationships as a function of whether or not the participant is performing a task during the scan. Thus, the goals of the present study were threefold: (1) assess whether dynamic connectivity (neural flexibility) during both resting as well as task-based scans is related to participant age and cognitive performance in a lifespan aging sample, (2) determine whether neural flexibility moderates relationships between age and cognitive performance, and (3) explore differences in neural flexibility between rest and task. Participants in the study were 423 healthy adults between the ages of 20-80 who provided resting state and/or task-based (Matrix Reasoning) functional magnetic resonance imaging (fMRI) scan data as part of their participation in two ongoing studies of cognitive aging. Neural flexibility measures from both resting and task-based scans reflected the number of times each node changed network assignment, and were averaged both across the whole brain (global neural flexibility) as well as within nine somatosensory/cognitive networks. Results showed that neural flexibility during the task was higher in older adults, and that neural flexibility in Default Mode and Visual networks was negatively related to performance on the Matrix Reasoning task. Resting state neural flexibility was not significantly related to either participant age or cognitive performance. Additionally, no neural flexibility measures that significantly moderated relationships between participant age and cognitive outcomes. Further, neural flexibility differed as a function of scan type, with resting state neural flexibility exhibiting significantly more variability than task-based neural flexibility. Thus, neural flexibility measures computed during a cognitive task may be more strongly related to cognitive performance across the adult lifespan, and are more sensitive to the effects of participant age on brain organization.

Characterizing intrinsic functional connectivity in relation to impaired self-regulation in intellectually able male youth with autism spectrum disorder

Autism ◽  
2020 ◽  
Vol 24 (5) ◽  
pp. 1201-1216 ◽  
Author(s):  
Hsiang-Yuan Lin ◽  
Hsing-Chang Ni ◽  
Wen-Yih Isaac Tseng ◽  
Susan Shur-Fen Gau
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Young People ◽  
Cognitive Control ◽  
Resting State ◽  
Self Regulation ◽  
Neural Correlates ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Sensorimotor Processing

While a considerable number of youth with autism spectrum disorder exhibit impaired self-regulation (dysregulation), little is known about the neural correlates of dysregulation in autism spectrum disorder. In a sample of intellectually able boys with autism spectrum disorder (further categorized as those with and without dysregulation) and typically developing boys (aged 7–17 years), we conducted a multivariate connectome-wide association study to examine the intrinsic functional connectivity with resting-state functional magnetic resonance imaging. Dysregulation was defined by the sum of Attention, Aggression, and Anxiety/Depression subscales on the Child Behavior Checklist. We identified that both categorical and dimensional neural correlates of dysregulation in youth with autism spectrum disorder involved atypical connectivity among the components of multiple brain networks, especially between those subserving sensorimotor processing and salience encoding, beyond higher-level cognitive control circuitries. Interaction within the attention network might serve as autism spectrum disorder–specific neural correlates underpinning dysregulation. Our results highlight that the inter-individual variability in dysregulation might contribute to the inconsistency in the neuroimaging literature of autism spectrum disorder. Collectively, the present findings provide evidence to suggest that dysregulation might be considered as both categorical and dimensional moderators to parse heterogeneity of autism spectrum disorder. Lay Abstract Impaired self-regulation (i.e., dysregulation in affective, behavioral, and cognitive control), is commonly present in young people with autism spectrum disorder (ASD). However, little is known about what is happening in people’s brains when self-regulation is impaired in young people with ASD. We used a technique called functional MRI (which measures brain activity by detecting changes associated with blood flow) at a resting state (when participants are not asked to do anything) to research this in intellectually able young people with ASD. We found that brains with more connections, especially between regions involved in sensorimotor processing and regions involved in the processes that enable peoples to focus their attention on the most pertinent features from the sensory environment (salience processing), were related to more impaired self-regulation in young people with and without ASD. We also found that impaired self-regulation was related to increased communication within the brain system involved in voluntary orienting attention to a sensory cue (the dorsal attention network) in young people with ASD. These results highlight how different people have different degrees of dysregulation, which has been largely overlooked in the earlier brain imaging reports on ASD. This might contribute to understanding some of the inconsistencies in the existing published literature on this topic.

scholarly journals Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Symptom Severity ◽  
Transition Probability ◽  
Feature Selection Method ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Dynamic Functional Connectivity ◽  
Default Mode

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

scholarly journals Resting State Functional Connectivity Predicts Future Changes in Sedentary Behavior

2021 ◽  
Author(s):  
Timothy P. Morris ◽  
Aaron Kucyi ◽  
Sheeba Arnold Anteraper ◽  
Maiya Rachel Geddes ◽  
Alfonso Nieto-Castañon ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Exercise Intervention ◽  
Supplementary Motor Area ◽  
Anterior Insula ◽  
Motor Area ◽  
Anterior Cingulate ◽  
Sedentary Behaviors ◽  
Resting State Functional Connectivity ◽  
The Right

AbstractInformation about a person’s available energy resources is integrated in daily behavioral choices that weigh motor costs against expected rewards. It has been posited that humans have an innate attraction towards effort minimization and that executive control is required to overcome this prepotent disposition. With sedentary behaviors increasing at the cost of millions of dollars spent in health care and productivity losses due to physical inactivity-related deaths, understanding the predictors of sedentary behaviors will improve future intervention development and precision medicine approaches. In 64 healthy older adults participating in a 6-month aerobic exercise intervention, we use neuroimaging (resting state functional connectivity), baseline measures of executive function and accelerometer measures of time spent sedentary to predict future changes in objectively measured time spent sedentary in daily life. Using cross-validation and bootstrap resampling, our results demonstrate that functional connectivity between 1) the anterior cingulate cortex and the supplementary motor area and 2) the right anterior insula and the left temporoparietal/temporooccipital junction, predict changes in time spent sedentary, whereas baseline cognitive, behavioral and demographic measures do not. Previous research has shown activation in and between the anterior cingulate and supplementary motor area as well as in the right anterior insula during effort avoidance and tasks that integrate motor costs and reward benefits in effort-based decision making. Our results add important knowledge toward understanding mechanistic associations underlying complex sedentary behaviors.

scholarly journals Predicting dysfunctional age-related task activations from resting-state network alterations

2019 ◽  
Author(s):  
Ravi D. Mill ◽  
Brian A. Gordon ◽  
David A. Balota ◽  
Jeffrey M. Zacks ◽  
Michael W. Cole
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Functional Connectivity ◽  
Resting State ◽  
Cognitive Task ◽  
Low Risk ◽  
Flow Modeling ◽  
Resting State Functional Connectivity ◽  
Age Related

AbstractAlzheimer’s disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the timecourse of illness. Study of these fMRI correlates of unhealthy aging has been conducted in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC network alterations associated with Alzheimer’s disease disrupt the ability for activations to flow between brain regions, leading to aberrant task activations. We apply this activity flow modeling framework in a large sample of clinically unimpaired older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) risk factors for AD. We identified healthy task activations in individuals at low risk for AD, and then by estimating activity flow using at-risk AD restFC data we were able to predict the altered at-risk AD task activations. Thus, modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy aged activations. These results provide evidence that activity flow over altered intrinsic functional connections may act as a mechanism underlying Alzheimer’s-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights linking restFC with cognitive task activations, this approach has potential clinical utility as it enables prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.Significance StatementDeveloping analytic approaches that can reliably predict features of Alzheimer’s disease is a major goal for cognitive and clinical neuroscience, with particular emphasis on identifying such diagnostic features early in the timeline of disease. We demonstrate the utility of an activity flow modeling approach, which predicts fMRI cognitive task activations in subjects identified as at-risk for Alzheimer’s disease. The approach makes activation predictions by transforming a healthy aged activation template via the at-risk subjects’ individual pattern of fMRI resting-state functional connectivity (restFC). The observed prediction accuracy supports activity flow as a mechanism linking age-related alterations in restFC and task activations, thereby providing a theoretical basis for incorporating restFC into imaging biomarker and personalized medicine interventions.

Inter-Hemispherical Investigations on the Functional Connectivity in Controls and Autism Spectrum Using Resting State fMRI

2020 ◽  
pp. 169-186
Author(s):  
S. Vidhusha ◽  
A. Kavitha
Keyword(s):  
Functional Connectivity ◽  
Granger Causality ◽  
Resting State ◽  
Cognitive Task ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Control Group ◽  
Neural Connectivity ◽  
Activation Patterns ◽  
The Brain

Autism spectrum disorders are connected with disturbances of neural connectivity. Functional connectivity is typically examined during a cognitive task, but also exists in the absence of a task. While a number of studies have performed functional connectivity analysis to differentiate controls and autism individuals, this work focuses on analyzing the brain activation patterns not only between controls and autistic subjects, but also analyses the brain behaviour present within autism spectrum. This can bring out more intuitive ways to understand that autism individuals differ individually. This has been performed between autism group relative to the control group using inter-hemispherical analysis. Indications of under connectivity were exhibited by the Granger Causality (GC) and Conditional Granger Causality (CGC) in autistic group. Results show that as connectivity decreases, the GC and CGC values also get decreased. Further, to demark the differences present within the spectrum of autistic individuals, GC and CGC values have been calculated.

scholarly journals Effects of long-term cocaine self-administration on brain resting-state functional connectivity in nonhuman primates

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Stephen J. Kohut ◽  
Dionyssios Mintzopoulos ◽  
Brian D. Kangas ◽  
Hannah Shields ◽  
Kelly Brown ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processing ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Resting State Functional Connectivity ◽  
Self Administration ◽  
Chronic Cocaine

AbstractLong-term cocaine use is associated with a variety of neural and behavioral deficits that impact daily function. This study was conducted to examine the effects of chronic cocaine self-administration on resting-state functional connectivity of the dorsal anterior cingulate (dACC) and putamen—two brain regions involved in cognitive function and motoric behavior—identified in a whole brain analysis. Six adult male squirrel monkeys self-administered cocaine (0.32 mg/kg/inj) over 140 sessions. Six additional monkeys that had not received any drug treatment for ~1.5 years served as drug-free controls. Resting-state fMRI imaging sessions at 9.4 Tesla were conducted under isoflurane anesthesia. Functional connectivity maps were derived using seed regions placed in the left dACC or putamen. Results show that cocaine maintained robust self-administration with an average total intake of 367 mg/kg (range: 299–424 mg/kg). In the cocaine group, functional connectivity between the dACC seed and regions primarily involved in motoric behavior was weaker, whereas connectivity between the dACC seed and areas implicated in reward and cognitive processing was stronger. In the putamen seed, weaker widespread connectivity was found between the putamen and other motor regions as well as with prefrontal areas that regulate higher-order executive function; stronger connectivity was found with reward-related regions. dACC connectivity was associated with total cocaine intake. These data indicate that functional connectivity between regions involved in motor, reward, and cognitive processing differed between subjects with recent histories of cocaine self-administration and controls; in dACC, connectivity appears to be related to cumulative cocaine dosage during chronic exposure.

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